Capability

Memory and code intelligence for agents

Agents that remember across sessions and explain code without inventing it

Rust · tree-sitterPostgreSQL and RedisInside FAFOHive
One surface · the model reads the map
19,000files in one multi-language index
  • 294,033of 294,362 code chunks covered by the computed graph
  • 0models involved in a dependency trace; it is a bounded database traversal
  • 3indexes, code, past decisions and reference documents, behind one retrieval surface

Coding agents forget everything between sessions, rediscover the same facts about a codebase daily, and explain call paths that do not exist with complete confidence.

I built the memory and code-intelligence service every agent in my estate connects to. Dependency tracing is a graph query, and the code explainer narrates only edges the graph has proven and refuses when coverage is incomplete. Start with A code explainer that is not allowed to invent.

Compute first, narrate second

The anchor, a bounded traversal and the code on the path (in green) come from the parser and SQL; the model then narrates exactly that path. An edge enters the graph only when both its ends are indexed, and graph generations keep a half-built graph from being served.

The hollow node is a file the graph does not cover: a query that touches it returns coverage incomplete, with no free-form fallback.

One multi-language index over the monorepo: Rust, Python, C#, TypeScript and more.

A refusal beats a plausible guess, because the caveat is the first thing a reader stops seeing.

Session memory captures every tool call, extracts what matters, and re-injects it later.

Three sessions, one memory
a tool call, captured as an observation
extracted, embedded, and re-injected where it is relevant

Very long sessions are compressed rather than truncated. The same observation search reaches stored decisions and fixes, so a settled question is found before it is re-debugged.

The capture layer is my Rust re-implementation of an open-source session-memory plugin; the plugin is credited on the FAFOHive page.